Instructions to use luqh/ClinicalT5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use luqh/ClinicalT5-base with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("luqh/ClinicalT5-base") model = AutoModelForSeq2SeqLM.from_pretrained("luqh/ClinicalT5-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9f6bf4678f15f07bd77f5d7d1a5a216be97d55dc0ee32e00f286a82c442d43a8
- Size of remote file:
- 892 MB
- SHA256:
- 10196e066b625ad70344b0eeab9a7022f8e324fdc8412bb8b8974a99ffc8ff1d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.